Real world planning applications typically involve making decisions that consumes limited resources, which requires both planning and scheduling. In this paper we propose a new approach that bridges the gap between planning and scheduling by explicitly modeling the problem in terms of resources, state variables and actions. We show that it is an intuitive way to formulate real world problems with complex constraints, and that solutions can be found by compiling the problem into a constraint satisfaction problem.